From Interactive to Adaptive Mood-Based Music Listening Experiences in Social or Personal Contexts

摘要

Consumer cultures are increasingly shifting to cultures of participation supported by technology such as social computing. In the domain of interactive audio, listeners' roles are revisited giving more importance to desire, context, and the sense of control. We present new developments in our mood-driven music player Moodplay allowing both social (virtual jukebox) and personal usage. Moodplay relies on semantic computing technologies for musical mood using social tags and informative and aesthetic browsing visualizations. The prototype runs with a dataset of over 10,000 songs covering various genres and arousal and valence levels. Changes in the design of the system were made in response to a user evaluation including over 120 participants from 15 different sectors of work or education. The proposed client/server architecture integrates modular components powered by semantic web technologies and audio content feature extraction. This enables a shift from interactivity to adaptivity where recorded music content can be controlled in flexible and non linear ways.